The hydrologic impacts associated with urban development are well documented and include a decline in downstream receiving water quality. Increased peak and total stormwater runoff volumes are the result of impervious development and decreased potential for surface infiltration. Additional water quality impairments are linked to the elevated generation and surface water transport of sediment, nutrients, bacteria, metals, pesticides, and other chemicals derived from urban land uses.
Urban municipalities expend resources to reduce non-point source urban pollutant loading to receiving waters and include a suite of non-structural and structural best management practices (BMPs). Non-structural BMPs focus on source control and pollution prevention, including street sweeping programs and parcel runoff controls like rain barrels or disconnected downspouts. Structural BMPs are physical features installed on the landscape to reduce stormwater runoff volumes and treat stormwater pollutants. Structural BMPs include low impact developments (LIDs) and green infrastructure BMPs such as infiltration or bio-retention features, as well as larger scale centralized BMPs such as dry basins or treatment vaults.
There are significant challenges in implementing an appropriate experimental design and data analysis procedure to confidently isolate pollutant load reductions attributable to a single or a suite of conservation efforts. One challenge is related to the lag time between the implementation of effective actions and the measurable response in the receiving waters beyond hydrologic variability. This lag time limits the immediate use of water quality data to guide impending decisions and stormwater program adjustments. The critical concept of maximizing the ability to make inferences about surface water health and minimizing the influences of natural seasonal or geographic variations are often overlooked. Such oversights can elevate data collection, management, and laboratory costs at the expense of developing a reliable and rigorous sampling and post-sampling procedure. If not well planned, sampling strategies can introduce ambiguity to measurements and reduce confidence that changes in pollutant loads over time can be attributed to management actions. Collection of water quality and hydrologic data is costly, complicated, and inherently spatially and temporally limited. Stormwater managers continue to struggle with how to effectively incorporate monitoring data and results into annual resource allocation decisions. Stormwater modeling allows for the simulation of a range of potential hydrologic conditions and the spatial aggregation of water quality benefits from multiple structural and non-structural BMPs. The use of a wide array of urban hydrology models to inform both short and long-term stormwater programmatic planning decision is common.